track.py 文件源码

def trainModel(featureCount, imageCount, save):
    clf = RandomForestRegressor(n_estimators=1, n_jobs=-1)

    features = generateFeatures(featureCount)

    for image in range(0, imageCount):
        print "Image " + str(image)
        train(clf, features, image)

    clf = clf.fit(X, Y)
    model = (clf, features)

    if save:
        joblib.dump(model, "model.pkl")

    return model